Procedures for recovering mesospheric and stratospheric temperatures from OSIRIS scattered-sunlight measurements
Bibliographic record
Abstract
Procedures for recovering mesospheric and stratospheric temperature profiles from scattered-sunlight limb radiance measurements made by the OSIRIS (optical spectrograph and infrared imager system) instrument on the Odin satellite are described. We assess various approaches to the problem and show that temperature recoveries based on an analysis of inferred volume-scattering rates are significantly more accurate than those based on direct analysis of the observed limb radiances. A forward model for the OSIRIS instrument is used to test temperature recovery algorithm performance in the presence of realistic instrument noise and to assess the expected accuracy of the OSIRIS temperature recoveries. It is shown that, for radiances measured in the near-infrared region, temperatures can be reliably recovered over the altitude range 40 km to 80 km with an accuracy of better than ±1 K. PACS Nos.: 42.68Mj, 94.10Dy
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.003 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".